TMET-23. MASS SPECTROMETRY-BASED METABOLIC PROFILING AND IMAGING OF ASTROCYTE AND GLIOBLASTOMA INVASIVE MARGIN CELLS

Abstract

Abstract Despite multimodal treatment, 90% of patients diagnosed with isocitrate dehydrogenase (IDH) wild-type glioblastoma experience tumour recurrence within 5 years. Poor prognosis is in considerable part attributed to the ability of cancer cells to infiltrate a healthy brain. We hypothesise that metabolic changes underpinning cellular crosstalk between astrocytes and glioblastoma cells isolated from the invasive margin within a physiologically representative in-vitro tumour microenvironment may reveal therapeutic targets to prevent or delay glioblastoma recurrence. This study used advanced analytical techniques to establish baseline metabolomic profiles for eGFP-tagged primary glioblastoma cells isolated from the invasive margin and healthy human cortical astrocytes. Liquid chromatography-mass spectrometry (LC-MS) enabled detailed analysis of biochemical pathways, and Atmospheric Pressure-Matrix Assisted Laser Desorption/Ionisation (AP-MALDI) imaging offered spatial localization of metabolites, critical for mapping their distribution within tumour microenvironments. Metabolites were extracted using a biphasic method (methanol:chloroform:water) for LC-MS analysis, and metabolic profiling was conducted using a ZIC-pHILIC column coupled with a Q-Exactive Orbitrap Mass Spectrometer. Additionally, AP-MALDI imaging facilitated the generation of high-resolution spatial distribution maps of selected metabolites, achieving a resolution of 10 µm. Both multivariate and univariate statistical analyses were applied to identify significant metabolic alterations. Metabolic profiling identified distinct pathways altered in glioblastoma cells compared to astrocytes, including alterations in aspartate, glycine and serine, and lipid metabolism. High-resolution imaging outlined the spatial distribution of metabolites involved in these pathways, revealing regions of metabolic heterogeneity. Furthermore, this methodology facilitated an expanded identification range of essential biomolecules, notably lipids and amino acids, thereby augmenting our understanding of their dynamic functions across diverse cellular contexts. By leveraging the complementary strengths of LC-MS and AP-MALDI imaging, this research enhances our understanding of spatial metabolite distribution in glioblastoma cells isolated from the invasive margin and suggests potential applications in patient tissue, offering a deeper exploration of disease mechanisms.